Epidemiological and genetic approaches to explore risk factors for pre-eclampsia
Bibliographic record
Abstract
Problem: Pre-eclampsia (PE) is a pregnancy complication that occurs in 3-10% of pregnancies world-wide, and it is characterized by high blood pressure and proteinuria. HELLP (Hemolysis, Elevated Liver enzymes, and Low Platelets syndrome) is a form of severe PE. Both environmental and genetic factors contribute to the etiology of PE. The overall goal of my thesis was to investigate how epidemiologic and genetic factors play a role in PE. My thesis has two parts. In Part I, I investigated epidemiologic risk factors of HELLP syndrome, with a focus on pre-pregnancy body-mass-index (BMI) and gestational-age specific rates. In Part II, I took a multi-omic approach to identify methylation-quantitative trait loci (mQTLs), which are genetic loci associated with nearby DNA methylation, in the human placenta. Altered DNA methylation in the placenta has been associated with PE, however, the contribution of genetics to such DNA methylation changes are understudied. Methods: Data for Part I were acquired from the BC Perinatal Database Registry, which included nearly all births in British Columbia, and 1100 severe PE cases collected from 2008-2019. Data for Part II were acquired from four independent cohorts, EPIC (Vancouver), CARMA-Preg (Vancouver), RICHS (Rhode Island), and NICHD (New York). A regional analysis of mQTLs in the CCR5 gene, which has been associated with PE, was performed, and associations with birth weight were tested. This was followed by a genome-wide search, which identified reproducible mQTLs, and investigated the influence of ancestry and ethnicity in mQTL testing. Conclusions: Elevated pre-pregnancy BMI was positively associated with HELLP syndrome, and this association was stronger with early-onset HELLP syndrome (occurring at <34 weeks). mQTLs in CCR5 were identified and genotypes were associated with birth weight. I also identified a subset of mQTLs genome-wide that were reproducible between cohorts and confirmed an enrichment for HLA-linked loci. A subset of SNP-CpG associations differed by ethnicity/ancestry of the population sample. The majority of PE-associated CpGs were found to be mQTLs, emphasizing the need to consider genetic background when using DNAm based approaches to predict PE. These two complementary approaches allowed further understanding of genetic and non-genetic risk factors of PE.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".